Why is it that many great technologies have actually been around for a long while, yet they don’t actually “make it” in the market until many years later, when it has improved to the point of being useful. For a few examples look at tablets, digital cameras, cloud computing, and even AI (artificial intelligence). Oftentimes, at least with software, the computing power needed a serious boost before consumers would accept such a clunky object. Where does this play in now, with eCommerce AI. It’s certainly something that many have used for quite a while but the true effects and benefits were minimal in part from computing power, and in part because of simple limitations in the coding being used to make the algorithms work properly. Now, we see a new advancement in AI, specifically in commerce technology that allows the computer to figure out based on the input what relates to that which the consumer is looking for, without them even knowing it many times. This is the new intersection of man and machine and it’s quickly becoming reality. So, how does the advancement in technology and computation power influence eCommerce AI?
For starters, look at the classic eCommerce system, which, has certainly gotten better over time, but still lacks the true technological wizardry needed to cut through the clutter. Our classic eCommerce system may be able to sort and organize our products and categories. It may even be able to organize the shipping and order management, and in some cases, it can even do omnichannel smooth. That being said, when is the last time your commerce system made the correlation with what a potential customer shared on their social media profile to what you have available in stock while they were on your site? And, when did what they searched for in Google to deliver a more relevant product suggestion straight to their email when that same customer was within 1 mile of your store? The chances are, it was never because most retailers are utilizing legacy, outdated systems. It is with this foresight that eCommerce AI takes shape and it makes all the previous questions a while lot easier to answer thanks to computers.
Ecommerce AI is at the heart a decision-making mechanism which takes advantage of human input at the forefront to decide what decisions to make when more data is provided. To give a bit more background on eCommerce AI and more specifically artificial intelligence as a whole it works off machines “mimicking” the cognitive aspect of the human mind. The machine works similar to the human mind to problem-solve and learn. More importantly, artificial intelligence can combine new factors to form new conclusions given additional inputs. The applications of this technology can be seen throughout a wide spectrum of processes such as fraud protection at banks, game strategy such as Chess and Go, prediction of the stock market, simulations in architecture and space, robotics and beyond. With this as the background, the use of eCommerce AI is relatively new in its adaptation. We can now use eCommerce AI all along the supply chain. From predicting trends and supply need’s, to automatically arranging new orders for demand sensitive products. We can also use these machine algorithms to help us determine the most efficient shipping routes and box sizes for packages (how do you think Amazon does it?). In addition, toward the end of the supply chain, we can predict when and what customers will need for their everyday household supplies. Ecommerce AI is something that extends even more precisely when talking about the ordering and suggestion of products to consumers.
In the most renowned sense of eCommerce AI it helps merchants automatically convert more customers, but how? In Epic Commerce, for instance, we can narrow down the suggestion of products to customers based on thousands of variables, all based on data-backed decisions. This helps retailers deal with the increasingly complex consumer, without having to manually make these decisions for consumers. Instead, we now tell the machine what things to compare (past purchases, social media profiles, cart abandonment, location, referral, email opens, past search history) and how you want to correlate this with on-site behavior. From here, through a series of “generated” decisions by the eCommerce AI algorithm you now have an automated engine learning about your customers and presenting the most highly relevant products to each potential or existing customer coming to your website/app or store. Given a certain pattern or event (which we call decision guides) the eCommerce AI will present this option to customers through on-site behavior, or through messages (email, SMS, ads etc.). The eCommerce AI benefits is because there is no limit on the number of decisions it can make, and the logic can extend far beyond a simple yes/no decision. In fact, the engine can calculate and provide in-depth decisions which may run several levels. When this happens, the eCommerce AI engine is taking multiple data points into account all at once to deliver the most relevant event-based product recommendations. How complex can it get? As complex as you make it. You could have a highly specific segment of users that you want to only target when they have added more than $100 to their cart, who are within <1 mile of your store, who have purchased shoes before, and who have liked a specific brand online. The event which comes out of this decision is going to be highly relevant to a very small segment of consumers, who are the most likely to buy based on all the criteria being mentioned. This is all well and good but how can you apply eCommerce AI to the classic eCommerce system you are using?
This is where systems like Epic Commerce come into play. Rather than having to replace your whole system (though it certainly might be more effective) you can simply connect in via API (application programming interface), to still utilize your data while making the most effective decisions. There are not a lot of systems like this, however in the new economy, API’s rule so it makes sense to be able to easily connect Shopify, Magento, Big Commerce etc. In addition to this, as mentioned, eCommerce AI takes multiple data points into account so rather than having to switch everything again, you can utilize the services you already use like Mailchimp, Buffer, Stripe, and others to automatically connect these in. What does this do, it enables the system to pull information about consumers from your email opens, social profiles, and purchase history, so it can be utilized effectively through the eCommerce AI algorithm. One place, all access equals intelligent eCommerce AI for both consumers and businesses alike. But, are consumers really benefiting?
The short answer: yes. It’s important to see that not only is eCommerce AI technology helping businesses succeed, but it attracts customers, and delivers a better buying experience all along the way. If a customer is shopping, chances are they want to buy something. How can we help them? Make the buying process as easy as possible. This is something machines have a habit of making much easier, particularly when it comes to eCommerce. While some shoppers may still prefer the human touch, there exists a comfortable line with customers to integrate human/machines. Let’s look at a few use cases. Perhaps one shopper was searching around for a particular brown shoe, finding it incredibly hard to find, they end up stumbling upon your store (from SEO AI?). Immediately the system picks up on their search quest, and present a notification-like alert that this very shoe is available online, and they could have it today if they are willing to drive the 1.2 miles to your store? While this is a rather particular use case, it represents the effectiveness of presenting the better option for consumers. Going further we’ve seen an explosion of messaging apps, particularly Facebook messenger. Well, imagine this customer lands on your site with the same search history, you could have your messenger bot present this shoe to them of a slightly different kind of shoe, with a special discount when they buy today. This may not always be able to convert this customer, but it is helpful for the customer nonetheless. Chances are the customer wouldn’t have even considered the shoe being presented, but when you present it in an intelligent manner with eCommerce AI this customer may make the choice to buy. This actually happens more often than not. If you think about your own buying habits, many times we go into a store with an idea of what we want, but when the clerk comes over and presents an equal or better option, we go for that mainly out of convenience. So, while not every purchase is going to happen from a recommendation, it sure increases the odds (by about 30% we’ve found from our own internal data crunching). Multiple this over thousands of customers, and you can see how it makes a difference in how customers are able to shop with you.
After a bit of digging, the facts are all over the internet, but this nice infographic does a nice job of presenting the facts from a wide segment of eCommerce AI. This infographic is from Entrepreneur magazine, produced by Red Stag Fulfillment. For more information or to see how your operations might be affected by eCommerce AI, reach out to one of our email@example.com who will get you to the next level. Alternatively, you can read about Epic Commerce here to see if it might be a fit for you (as many situations are unique, there’s more information available talking with a firstname.lastname@example.org but this will get you started).